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RTB House — Data Analyst Technical Challenge

This repository contains my solution to the RTB House Data Analyst technical challenge. The analysis covers campaign performance data from one of RTB House's clients, spanning January to November 2025.

Repository Structure

notebooks/
├── rtb_analysis_process.ipynb       # Questions 1 and 2 — metric calculations and performance analysis
└── sql_case_solutions.ipynb         # Questions 4, 5 and 6 — SQL queries
presentation/
└── rtb_house_performance_analysis.pdf  # Question 2 — insights and findings presented as PDF
data/                                # Source data files
database/                            # Database schema and setup
docker-compose.yml                   # PostgreSQL local environment
requirements.txt
README.md

Questions Addressed

File Questions
rtb_analysis_process.ipynb 1 — Metric calculations (CTR, CPC, CR, ROAS, AOV, Share) and 2 — Performance analysis and insights
sql_case_solutions.ipynb 4, 5 and 6 — SQL queries
rtb_house_performance_analysis.pdf 2 — Insights presented as pdf

How to Run

Requirements pip install -r requirements.txt

Database setup docker-compose up -d

Notebooks Open and run the notebooks in order:

  1. rtb_analysis_process.ipynb — data analysis and visualizations
  2. sql_case_solutions.ipynb — SQL queries using the provided schema

Tech Stack

Python · pandas · matplotlib · seaborn · SQLAlchemy · psycopg2 · PostgreSQL 13 · Docker · Jupyter Notebook

Notes

  • Data covers January to November 2025. December is not included in the dataset.
  • All monetary values are in BRL.
  • SQL queries were written and tested against the schema provided in the database tab.
  • PostgreSQL runs locally via Docker Compose. Make sure Docker is running before executing the SQL notebook.